package net.bwie.realtime.jtp.dws.log2.job2;

import net.bwie.realtime.jtp.dws.log2.util2.AnalyzerUtil;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.table.annotation.DataTypeHint;
import org.apache.flink.table.annotation.FunctionHint;
import org.apache.flink.table.api.EnvironmentSettings;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableEnvironment;
import org.apache.flink.table.functions.TableFunction;
import org.apache.flink.types.Row;

import java.util.List;

public class JtpTrafficSearchKeywordMinuteWindowDwsJob2 {
    public static void main(String[] args) {
        //1.表执行环境
        TableEnvironment tabEnv=getTableEnv();

        //2.输入表-input:映射到kafka消息队列
        createInputTable(tabEnv);

        //3.数据处理-select
        Table reportTable=handle(tabEnv);
        
        //4.输出表-output:映射到doris表
        createOutputTable(tabEnv);

        //保存数据-insert
        saveToSink(tabEnv,reportTable);
    }

    private static void saveToSink(TableEnvironment tabEnv, Table reportTable) {
        //a.注册Table为表，给以表名称
        tabEnv.createTemporaryView("report_table",reportTable);
        //b.查询-插入
        tabEnv.executeSql(
                "INSERT INTO dws_traffic_search_keyword_window_report_doris_sink\n" +
                        "SELECT\n" +
                        "    SUBSTRING(CAST(window_start_time AS STRING),0,19) AS start_time\n" +
                        "    ,SUBSTRING(CAST(window_end_time AS STRING),0,19) AS end_time\n" +
                        "    ,SUBSTRING(CAST(window_start_time AS STRING),0,19) AS cur_time\n" +
                        "    ,keyword\n" +
                        "    ,keyword_count\n" +
                        "FROM report_table"
        );
    }

    private static void createOutputTable(TableEnvironment tabEnv) {
        tabEnv.executeSql(
                "CREATE TABLE dws_traffic_search_keyword_window_report_doris_sink(\n" +
                        "    `window_start_time` STRING COMMENT '窗口开始日期时间',\n" +
                        "    `window_end_time` STRING COMMENT '窗口结束日期时间',\n" +
                        "    `cur_date` STRING COMMENT '分区日期',\n" +
                        "    `keyword` STRING COMMENT '搜索关键词',\n" +
                        "    `keyword_count` BIGINT COMMENT '搜索关键词被搜索次数'\n" +
                        "    )WITH(\n" +
                        "    'connector'='doris',\n" +
                        "    'fenodes'='node102:8030',\n" +
                        "    'table.identifier'='jtp_realtime_report.dws_traffic_search_keyword_window_report'\n" +
                        "    'username'='root',\n" +
                        "    'password'='123456',\n" +
                        "    'sink.label-prefix'='doris_label'\n" +
                        ")"
        );
        
    }

    private static Table handle(TableEnvironment tabEnv) {
        //1.获取搜索词和搜索时间
        Table searchLogTable = tabEnv.sqlQuery(
                "SELECT\n" +
                        "    page['item'] AS  full_word\n" +
                        "    ,row_time\n" +
                        "FROM dwd_traffic_page_log_kafka_source\n" +
                        "WHERE page['item'] IS NOT NULL\n" +
                        "    AND page['last_page_id']='search'\n" +
                        "    AND page['item_type']='keyword'"
        );
        tabEnv.createTemporaryView("search_log_table",searchLogTable);

        //2.使用自定义UDTF函数，对搜索词进行中文分词
        tabEnv.createTemporarySystemFunction("ik_analyzer_udtf", IkAnalyzerFunction.class);
        Table wordLogTable = tabEnv.sqlQuery(
                "SELECT\n" +
                        "    full_word\n" +
                        "    ,keyword\n" +
                        "    ,row_time\n" +
                        "FROM search_log_table,\n" +
                        "     LATERAL TABLE (ik_analyzer_udtf(full_word)) AS T(keyword)\n"
        );
        tabEnv.createTemporaryView("word_log_table",wordLogTable);
        
        //3.设置窗口进行分组，聚合计算
        Table reportTable = tabEnv.sqlQuery(
                "SELECT\n" +
                        "    window_start AS window_start_time\n" +
                        "    ,window_end AS window_end_time\n" +
                        "    ,keyword\n" +
                        "    ,count(keyword) AS keyword_count\n" +
                        "FROM TABLE(\n" +
                        "             TUMBLE(TABLE word_log_table,DESCRIPTOR(row_time),INTERVAL '1' MINUTES)\n" +
                        "         ) t1\n" +
                        "GROUP BY window_start,window_end, keyword"
        );
        return reportTable;
    }


    private static void createInputTable(TableEnvironment tabEnv) {
        tabEnv.executeSql(
                "CREATE TABLE dwd_traffic_page_log_kafka_source\n" +
                        "(\n" +
                        "    `common` MAP<STRING, STRING> COMMENT '公共环境信息',\n" +
                        "    `page`   MAP<STRING, STRING> COMMENT '页面信息',\n" +
                        "    `ts`     BIGINT COMMENT '时间戳',\n" +
                        "    row_time AS TO_TIMESTAMP(FROM_UNIXTIME(ts / 1000, 'yyyy-MM-dd HH:mm:ss.SSS')) COMMENT '事件发生时间,指定格式',\n" +
                        "    WATERMARK FOR row_time AS row_time - INTERVAL '0' MINUTE\n" +
                        ") WITH (\n" +
                        "    'connector' = 'kafka',\n" +
                        "    'topic' = 'dwd-traffic-page-log',\n" +
                        "    'properties.bootstrap.servers' = 'node101:9092,node102:9092,node103:9092',\n" +
                        "    'properties.group.id' = 'gid_dws_traffic_search_keyword',\n" +
                        "    'scan.startup.mode' = 'earliest-offset',\n" +
                        "    'format' = 'json',\n" +
                        "    'json.fail-on-missing-field' = 'false',\n" +
                        "    'json.ignore-parse-errors' = 'true'\n" +
                        ")"
        );
    }

    private static TableEnvironment getTableEnv() {
        //1.环境属性设置
        EnvironmentSettings settings = EnvironmentSettings
                .newInstance()
                .inStreamingMode()
                .build();
        TableEnvironment tabEnv = TableEnvironment.create(settings);

        //2.配置属性设置
        Configuration configuration = tabEnv.getConfig().getConfiguration();
        configuration.setString("table.local-time-zone","Asia/Shanghai");
        configuration.setString("table.exec.resource.default-parallelism","1");
        configuration.setString("table.exec.state,ttl","5 s");
        configuration.setString("execution.checkpointing.interval","30 s");

        //3.返回对象
        return tabEnv;
    }

    @FunctionHint(output = @DataTypeHint("ROW<word STRING>"))
    public static class IkAnalyzerFunction extends TableFunction<Row> {
        public void eval(String fullWord) throws Exception {
            //中文分词
            List<String> list = AnalyzerUtil.ikAnalyzer(fullWord);
            //循环遍历输出
            for (String keyword : list) {
                collect(Row.of(keyword));
            }
        }

    }
}
